feat: add se_r descriptor

deepmd/pt/model/descriptor/__init__.py

@@ -13,6 +13,7 @@
 )
 from .env_mat import (
     prod_env_mat_se_a,
+    prod_env_mat_se_r,
 )
 from .gaussian_lcc import (
     DescrptGaussianLcc,
@@ -27,6 +28,9 @@
     DescrptBlockSeA,
     DescrptSeA,
 )
+from .se_r import(
+    DescrptSeR
+)
 
 __all__ = [
     "Descriptor",
@@ -35,9 +39,11 @@
     "DescrptBlockSeA",
     "DescrptBlockSeAtten",
     "DescrptSeA",
+    "DescrptSeR",
     "DescrptDPA1",
     "DescrptDPA2",
     "prod_env_mat_se_a",
+    "prod_env_mat_se_r",
     "DescrptGaussianLcc",
     "DescrptBlockHybrid",
     "DescrptBlockRepformers",

deepmd/pt/model/descriptor/env_mat.py

@@ -29,6 +29,27 @@ def _make_env_mat_se_a(nlist, coord, rcut: float, ruct_smth: float):
     env_mat_se_a = torch.cat([t0, t1], dim=-1) * weight
     return env_mat_se_a, diff * mask.unsqueeze(-1), weight
 
+def _make_env_mat_se_r(nlist, coord, rcut: float, ruct_smth: float):
+    """Make smooth environment matrix."""
+    bsz, natoms, nnei = nlist.shape
+    coord = coord.view(bsz, -1, 3)
+    nall = coord.shape[1]
+    mask = nlist >= 0
+    # nlist = nlist * mask  ## this impl will contribute nans in Hessian calculation.
+    nlist = torch.where(mask, nlist, nall - 1)
+    coord_l = coord[:, :natoms].view(bsz, -1, 1, 3)
+    index = nlist.view(bsz, -1).unsqueeze(-1).expand(-1, -1, 3)
+    coord_r = torch.gather(coord, 1, index)
+    coord_r = coord_r.view(bsz, natoms, nnei, 3)
+    diff = coord_r - coord_l
+    length = torch.linalg.norm(diff, dim=-1, keepdim=True)
+    # for index 0 nloc atom
+    length = length + ~mask.unsqueeze(-1)
+    t0 = 1 / length
+    weight = compute_smooth_weight(length, ruct_smth, rcut)
+    weight = weight * mask.unsqueeze(-1)
+    env_mat_se_r = t0 * weight
+    return env_mat_se_r, diff * mask.unsqueeze(-1), weight
 
 def prod_env_mat_se_a(
     extended_coord, nlist, atype, mean, stddev, rcut: float, rcut_smth: float
@@ -58,3 +79,32 @@ def prod_env_mat_se_a(
     t_std = stddev[atype]  # [n_atom, dim, 4]
     env_mat_se_a = (_env_mat_se_a - t_avg) / t_std
     return env_mat_se_a, diff, switch
+
+def prod_env_mat_se_r(
+    extended_coord, nlist, atype, mean, stddev, rcut: float, rcut_smth: float
+):
+    """Generate smooth environment matrix from atom coordinates and other context.
+
+    Args:
+    - extended_coord: Copied atom coordinates with shape [nframes, nall*3].
+    - atype: Atom types with shape [nframes, nloc].
+    - natoms: Batched atom statisics with shape [len(sec)+2].
+    - box: Batched simulation box with shape [nframes, 9].
+    - mean: Average value of descriptor per element type with shape [len(sec), nnei, 1].
+    - stddev: Standard deviation of descriptor per element type with shape [len(sec), nnei, 1].
+    - deriv_stddev:  StdDev of descriptor derivative per element type with shape [len(sec), nnei, 1, 3].
+    - rcut: Cut-off radius.
+    - rcut_smth: Smooth hyper-parameter for pair force & energy.
+
+    Returns
+    -------
+    - env_mat_se_r: Shape is [nframes, natoms[1]*nnei*1].
+    """
+    nframes = extended_coord.shape[0]
+    _env_mat_se_r, diff, switch = _make_env_mat_se_r(
+        nlist, extended_coord, rcut, rcut_smth
+    )  # shape [n_atom, dim, 1]
+    t_avg = mean[atype]  # [n_atom, dim, 1]
+    t_std = stddev[atype]  # [n_atom, dim, 1]
+    env_mat_se_r = (_env_mat_se_r - t_avg) / t_std
+    return env_mat_se_r, diff, switch